Materials Data Scientist / Scientific Software Developer

Enthought

$110K — $130K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in materials science, chemistry, or a related field
  • Experience with machine learning and data-driven modeling
  • Proficiency in software development with AI tools
  • Ability to lead technical projects, directing autonomous agents
  • Strong analytical skills to solve complex R&D problems

Responsibilities

  • Design comprehensive materials informatics solutions based on client needs
  • Utilize AI coding assistants for rapid prototyping and development
  • Direct AI agents to tackle tasks in materials and chemistry research
  • Collaborate closely with clients to address research and product challenges
  • Build and integrate decision-support tools with user-friendly interfaces
  • Incorporate AI capabilities while ensuring data integrity and value
  • Participate in collaborative development and maintain data security

Benefits

  • Impact scientific breakthroughs in various fields
  • Work in an automation-centric environment with AI tools
  • Collaborate with talented scientists and engineers
  • Access to training programs in cutting-edge technology
  • Be part of a global culture with offices in multiple cities
  • Flexible hybrid working options
Full Job Description
We are hiring a Materials Data Scientist / Scientific Software Developer to join our client-facing solution delivery team. Working agent-first, you will pair deep materials and chemistry expertise with agentic AI coding tools to help industrial materials and chemical researchers make better, faster R&D decisions - building data-driven models, AI-based decision-support tools, and analysis pipelines.

Key Responsibilities
  • Design end-to-end materials informatics solutions - apply deep knowledge of materials science, chemistry, and machine learning to translate client R&D problems into architectures spanning data, models, and user-facing applications.
  • Work agent-first - use AI coding assistants and autonomous coding agents as your default way to explore data, prototype models, build software, write tests, and produce documentation, compressing the path from research question to working solution.
  • Direct AI agents like a technical lead - decompose materials and chemistry problems into well-scoped tasks, give agents the domain context and physical constraints they need, and iterate toward correct, defensible results.
  • Solve complex research and product-development problems in close collaboration with client researchers and business leaders.
  • Build data-driven models, AI-based decision-support tools, and automated analysis pipelines, and assemble them into web-based solutions involving GUIs, 2D and 3D graphics, and cloud computing.
  • Design AI-enabled and agentic capabilities into client solutions where they add value - including retrieval over materials data - held to the same rigor as any other component.
  • Apply judgment about where AI and generative approaches fit and where they don't, especially given the small, sparse, and noisy datasets typical of materials R&D.
  • Take part in collaborative development practices - code review, architecture reviews, sprint planning, retrospectives, and daily standups - and interface directly with clients to define, demonstrate, and refine solutions.
  • Handle client data and intellectual property responsibly, using AI tools only in approved, secure configurations.

What We Offer
  • Meaningful impact - your work directly advances scientific breakthroughs, from accelerating drug discovery to developing sustainable materials.
  • A front-row seat to agentic AI - work at an automation-first company where every role directs AI tools, and help define how the industry puts them to work.
  • World-class colleagues - collaborate with some of the smartest, kindest scientists and engineers around.
  • Continuous learning - access to Enthought's training programs in Python, machine learning, and scientific computing.
  • A global, collaborative culture across our Austin, Cambridge, and Tokyo offices.
  • Flexible hybrid work based out of our Austin office.
  • Competitive compensation and benefits.

#LI-Hybrid

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